Bring your data engineering expertise to a high-impact role focused on building reliable, scalable data solutions that support finance and AI initiatives. This position offers the opportunity to design modern pipelines, strengthen data quality and governance, and collaborate across technical and business teams in a fast-moving, enterprise environment.

Responsibilities

• Evaluate data sources, systems of record, reference data, documents, and operational datasets to support finance-related solutions.
• Assess data quality, completeness, lineage, sensitivity, and accessibility to ensure data is dependable and ready for use.
• Design and develop data pipelines, transformations, semantic layers, retrieval indexes, and reusable data products.
• Partner with AI teams to support retrieval-augmented generation approaches, embeddings, vector databases, grounding strategies, and refresh processes.
• Work closely with security, privacy, compliance, and governance stakeholders to support responsible data handling and control requirements.
• Create synthetic, masked, or de-identified datasets for development and testing needs.
• Implement data quality checks, validation controls, lineage documentation, and exception-handling processes.
• Support experimentation and measurement efforts by delivering reliable baseline and treatment datasets.
• Prepare documentation, operational handoff materials, and data assets for long-term ownership and support.

Skills

• 5+ years of experience in data engineering, data platforms, or a related technical field.
• Strong hands-on experience with SQL, APIs, ETL/ELT development, data integration, and batch or streaming data architectures.
• Experience working with cloud-based data platforms and large-scale data pipelines.
• Solid understanding of data modeling, data quality, metadata management, lineage, and governance practices.
• Familiarity with enterprise data security, privacy, access controls, and compliance considerations.
• Strong problem-solving skills with the ability to move quickly while maintaining quality, repeatability, and trust.
• Excellent communication and stakeholder management skills.
• Ability to work in a hybrid environment and attend onsite meetings or interviews when needed, including laptop pickup and ID verification if selected.

Preferred Skills

• Experience supporting finance domains such as FP&A, accounting, tax, treasury, or financial reporting.
• Exposure to AI, machine learning, or generative AI solutions in an enterprise setting.
• Familiarity with modern data governance, observability, and cataloging tools.
• Experience with semantic retrieval, document chunking, embeddings, vector databases, or feature preparation.
• Background supporting experimentation, control-group testing, or value measurement initiatives.

We value diversity, equity, and inclusion as core principles and are committed to fostering a welcoming environment where different perspectives and experiences are respected and valued. We encourage candidates from all backgrounds to apply and bring their unique strengths to the team.